System and method for manufacturing bolus for radiotherapy using a three-dimensional printer

ABSTRACT

Disclosed herein are systems, methods, and computer-readable storage devices for manufacturing patient-specific bolus for use in targeted radiotherapy treatment. Based on dose calculations without a bolus and based on three-dimensional scan data of a patient, the example system generates a model of a bolus for targeting radiotherapy treatment to a planning target volume or target region within the patient. The system can perform several iterations to generate a resulting model for the bolus. Then, the system can generate instructions for controlling a three-dimensional printer to generate the bolus that conforms to the patient&#39;s skin surface while also specifically targeting the planning target volume for the radiotherapy treatment. In this way, the amount of radiotherapy treatment administered to other tissue is reduced, while the costs, time, and human involvement in creating the bolus are significantly reduced.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Application No.PCT/CA2014/051128 (published as WO 2015/077881), filed on Nov. 26, 2014,which claims priority to U.S. Provisional Patent Application No.61/909,789, filed on Nov. 27, 2013; the contents of both applicationsare herein incorporated by reference in their entirety.

BACKGROUND

1. Technical Field

The present disclosure relates to manufacturing bolus for use inradiotherapy and more specifically to customized, user-specific bolusfor accurately targeting a specific treatment area. The disclosure alsoaddresses creating bolus for different types of therapy, includingphoton therapy, electron therapy, and proton therapy. The disclosurealso describes how a bolus can be incorporated into an immobilizationdevice, and how a custom, 3D-printed bolus can incorporate dosimeterfunctionality.

2. Introduction

Radiotherapy is a treatment for disease in which an affected part of thebody of a patient is exposed to ionizing radiation. For a range oftreatment applications, an adequate surface dose is required,particularly in the presence of superficial target volumes. Sincemegavoltage radiation beams do not deposit maximal dose at the skinsurface, in these cases surface dose can be increased by overlaying atissue equivalent material, called bolus. Bolus is most commonly used inconjunction with electron therapy which is well suited to treatment ofsuperficial lesions with a single beam. A second purpose of bolus iscontrolling the depth in tissue at which a therapeutic dose of radiationis deposited, and modulating this depth as a function of position acrossthe beam.

Currently, radiation therapists manually create bolus. For example, aradiation therapist can apply wax or thermoplastic sheets to the patientsurface. Often, a radiation therapist heats the wax or other material tomake it more pliable or malleable. The radiation therapist can apply thebolus material in one or more layers to conform to the patient surface.Often the radiation therapist attempt to manually create a regulargeometry or a flat surface at the location of beam incidence. Thepatient and radiation therapist must then wait while the bolus materialcools.

This manual approach is limited in regard to accuracy, practicality andquality of the delivered treatment. First, this process is laborintensive because it involves manual application of bolus material. Thisoccupies the patient, potentially multiple staff members, as well asclinic space, often in an expensive or valuable computed tomography (CT)suite. Second, the bolus should conform well to the patient skin, evenin situations where the geometry is complex, such as an outer ear,canthus, lip, or other extremities. The capacity of manually producedbolus to conform to irregular surfaces is limited. Inaccuracy of bolusfabrication can result in air gaps between the bolus and patientsurface. Air gaps, in turn, can result in substantial inaccuracies indelivered surface dose, for example, exceeding 10%. In practice, thissometimes prompts filling of air gaps with wet gauze, however thevariability in the wetness of the gauze causes inconsistency indelivered dose. Third, bolus is commonly pre-defined in the planningsystem as a water equivalent, uniform layer on the patient surface. Thesimilarity of the planned and fabricated bolus is limited with regard toboth thickness and curvature, particularly in the presence of steep,complex or curved surfaces. This compromises the accuracy of thedelivered dose distribution relative to the plan. Fourth, other thancontrolling the depth of penetration of an electron beam into tissue,manually manufactured bolus does not achieve conformity between theradiation dose and the target volume. Most commonly, the high doseregion will encompass the deepest aspect of an irregularly shaped tumorbut also a volume of surrounding healthy tissue which would bepreferable to avoid exposing to excess radiation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example bolus on an example patient surface;

FIG. 2 illustrates an example block diagram of an iterative approach tomanufacturing a bolus;

FIG. 3A illustrates an example of a 3D printed bolus;

FIG. 3B illustrates a cutaway view of the 3D printed bolus andcalculated dose distribution within a patient foot; and

FIG. 4 illustrates an example user interface for bolus design in aninitial, pre-design stage;

FIG. 5 illustrates the example user interface for bolus design duringdesign;

FIG. 6 illustrates an example immobilization support with an integratedbolus;

FIG. 7 illustrates an example method embodiment;

FIG. 8 illustrates an example system embodiment;

FIG. 9 illustrates an example bolus design calculation;

FIG. 10 illustrates an example schematic representation of bolus designalgorithm after first iteration;

FIG. 11 is an example schematic representation of regions involved insmoothing; and

FIG. 12 illustrates a graph of a ratio used in the calculation foradjusting the bolus design.

DETAILED DESCRIPTION

A system, method and computer-readable storage devices are disclosedwhich provide a way to plan radiotherapy treatment, such as with asingle electron beam or one or more photon beams, using computer modelsof the patient derived from three-dimensional imaging data, whiledelivering an adequate dose to the planning target volume (PTV) of thepatient while minimizing the dose to surrounding healthy tissues andnormal structures of the patient. Bolus can be custom manufactured forpatients to achieve this goal, such as with a three-dimensional printer.

The approach described herein can provide several advantages. Forexample, patients already undergo CT imaging for treatment planning. Theexample system can design bolus digitally with high accuracy andprecision based on this three dimensional data set without the patient'spresence. The system can design the bolus so that the upper (proximal)surface of the bolus enhances the dose conformity, dose homogeneity,dose uniformity, quality, or effective area of the radiation deliveredplan. Further, the system can manufacture the bolus using additivemanufacturing, such as three dimensional printing technology. Theprinted bolus may be manufactured using polylactic acid (PLA), which isbiocompatible. PLA is derived from starches (e.g. corn) and is alreadyused for medical implants in the form of screws, pins, rods, and mesh.

3D printing is a specific form of additive manufacturing. One of themost common methods of 3D printing, and the one explored in this work isFused Deposition Modeling (FDM). This process has recently has becomewidely accessible at low cost, such as MakerBot devices. 3D printinginvolves a fabrication process that uses a CAD model as input to createa 3D physical model by applying many successive layers of the chosenmaterial at a high resolution, such as a resolution of 100 micrometers,although the system can use other resolutions and capabilities.

3D printing provides several advantages over the manual approach tobolus fabrication. Bolus fabrication can be largely automated, and theprecision can be substantially improved. Because the fabrication isautomated, human error is reduced. Thus, 3D printed bolus can provideimproved conformity between bolus and patient surface, reducing thepossibility of air cavities which would degrade accuracy of treatment orwould provide a dosage above or below what is desired. PLA bolus isdurable, unlike traditional wax bolus materials. Increased durabilitycan be particularly important for treatment regimes with the bolus overan extended period of time, such as a regime of 30 daily treatments. Aprecisely generated bolus can provide a customized, highly conformaldose distribution for each individual patient based on his or herspecific needs and situation. 3D printing allows for a clinic or doctorto fabricate optimized bolus designs in-house rather than placing anorder to an off-site service which may be expensive or require a lengthywait. 3D printing can provide a cost reduction, time savings, improvedtreatment flexibility, and ability to respond to changing clinicaldemands by modifying the bolus design during the course of thetreatment.

Aside from these practical advantages, digital design and 3D printing ofbolus can also improve the delivered treatment. Currently, the electrontherapy planning process involves the selection of beam energy andelectron aperture dimensions to achieve adequate coverage of thePlanning Target Volume (PTV). 3D printing allows for customizing thepatient surface to optimize the shape of the dose distributions producedat a particular depth and region within the PTV. This concept isillustrated in FIG. 1. FIG. 1 illustrates an example configuration 100of a bolus 102 on an example patient surface 106 to treat a specific PTVregion 104. This example illustrates how the unique shape of the bolus102 can be tailored to provide treatment to a region 110 tightlysurrounding the PTV 104 rather than a larger region 108 associated withstandard treatment. The specific shape of the bolus 102 is tailored tomatch the PTV 104 very closely to avoid treating body tissues which areoutside of the PTV 104. When 3D printing bolus, the system can generatea patient-specific bolus without introducing any new steps for thepatient since the CT data is typically acquired as part of the treatmentplanning process.

A bolus 102 can be constructed for multiple different types of radiationtherapy. For example, a bolus 102 can be constructed for use in photontherapy, electron therapy, or proton therapy. The propagation and othercharacteristics of photons, electrons, and protons are different. Thus,different bolus shapes, sizes, thicknesses, and/or constructions can beused to target a treatment dose of radiation to a same body region usingdifferent radiation therapies.

Radiation therapy professionals can use a bolus for megavoltage photontherapy, particularly when a maximal dose is required at the patient'sskin. A 3D-printed bolus can be produced, based on measurements of thepatient's skin contours and the target treatment region within the body.With accurate measurements of the patient's skin and body contours, the3D-printed bolus can be shaped to mate accurately to the patientsurface, even in the presence of very complex geometries, such as theregions around the face, ears, or surgical cavities. As set forth above,while the patient-facing surface of the bolus is shaped based on thebody geometry, the non-patient facing surface of the bolus is shaped sothat radiation treatments, when applied from one or more points externalto the body through the bolus, are directed to affect only a specificdesired treatment target region within the body and/or at the surface ofthe skin.

However, due to differences in the way photons interact and/or propagatecompared to electrons and protons, it is difficult to control high-doseconformity (agreement between shapes of the high dose volume and thetarget) through the use of bolus. Therefore, the system can produce anaccurately fitting bolus of a thickness (or variable thickness, ifdesired) specified by a doctor or other radiation treatmentprofessional, to achieve the required dose of radiation treatment at thesurface. Any accurate photon dose calculation can be used in conjunctionwith this design process. In one example implementation, the system usesthe Anisotropic Analytic Algorithm (AAA, from Varian Medical), but manyother suitable algorithms exist and can be used interchangeably.Advantages of the approach include but are not limited to (i) bolusdesign from CT data, resulting in less human involvement in the boluscreation process, (ii) bolus conformity to complex surfaces (e.g.,surgical site post-mastectomy), and (iii) specification of thickness ordensity of bolus (which in turn controls the surface dose).

Since some of the most challenging and common scenarios for use of bolusinvolve electron beam therapy, many of the examples provided hereinfocus primarily on that application. While the design of the distalsurface (the surface mating to the skin) is based on CT data indicatingthe surface and contours of the patient, design of the bolus to targetthe PTV via the proximal surface is non-trivial. Electrons scatterwithin any medium in a complex way, and thus simple approaches such asray-tracing are not adequate. An algorithm for bolus design can achievespecific dosimetric goals. The system can incorporate this algorithm into a common treatment planning approach. The system can provide aninterface allowing production of the optimized bolus using 3D printing.The algorithm can operate in conjunction with an external beam planningsystem, obviating the need to re-implement a system accurate dosecalculation. The system can incorporate the electron Monte Carlo (eMC)algorithm. A block diagram 200 of an iterative approach of the algorithmis outlined in FIG. 2.

After calculating an initial dose distribution in absence of bolus 202,the treatment plan, CT set, structures and dose distribution areprovided to a system 204 implementing the algorithm. The system 204calculates an initial approximation of bolus design to achieve conformalcoverage of the target volume. The system can provide the bolus designback to the planning system for dose calculation with the bolus design206. The system can iterate this process in an automated fashion withsubsequent cycles also addressing more subtle aspects of improvement ofthe dose distribution, such as hot-spots, cool spots and optimization ofconformity at the edges of the target volume. For example, if the dosecalculation with bolus 206 is not acceptable 208, then the system 204can iterate on the bolus design again. Empirical evidence shows that 2-3iterations are usually sufficient to achieve high plan quality. If,however, the bolus design is acceptable 208, then the bolus can beexported, such as via an STL file format, to a bolus fabrication device210, such as a 3D printer. The bolus fabrication device 210 canmanufacture the bolus with minimal user intervention. Followingmanufacture, a doctor or radiation therapist can place the bolus on thepatient to confirm that the positioning and fit are proper. If desired,the doctor or radiation therapist can perform an additional CT scan withthe bolus in place to collect a final dose calculation with the actualmanufactured bolus. The example dose calculation 214 can operateaccording to the electron Monte Carlo (eMC) algorithm, but can bereplaced with any suitably accurate electron dose calculation algorithm.Similarly, for different types of radiation therapy, differentalgorithms can be applied, such as an algorithm for proton or photontherapy.

The bolus optimization and design system of FIG. 2 is modular, i.e. thebolus design portion 204 is isolated from the dose calculation portion202, 206. For proton therapy, the eMC electron calculation algorithm inthe treatment planning system could be replaced by a proton dosecalculation algorithm. Example algorithms for proton dose calculationmay be analytic or Monte Carlo. Some tuning of the bolus optimizationalgorithm would be required for use in proton therapy applications,notably the parameters of regional modulation and adjustment at PlanningTarget Volume margin. Some tuning of the bolus optimization algorithmmay be required for proton therapy applications, such as the regionalsmoothing operators to adjust for dose coverage at the distal surface ofthe PTV, hot- and cold-spots within the PTV, and coverage at the PTVmargins.

FIG. 9 illustrates a bolus design calculation. Bolus design iscalculated on a grid containing the isocenter and perpendicular tocentral axis. Bolus thickness is calculated using a grid size of 2.5 mmas default; however a finer grid can be used for improved precision.Structures exported from Eclipse (i.e., ‘bolus’, ‘PTV’, ‘Dose 90%’ and‘Hot Spot’ (if required)), are segmented into distal (i.e., deeper) andproximal (i.e., shallower) surfaces according to the maximum and minimumlateral coordinates. Ray lines are traced from the virtual source toeach point on the grid, and extended to the distal side of PTV and 90%isodose surfaces. For ray lines intersecting the PTV, the distancez_(real)=T₁T₂ is calculated.

Since patients typically contain tissue inhomogeneities, z_(real) isconverted to an effective distance z_(eff) using the coefficient ofequivalent thickness (CET) method. The effective shift of bolusthickness (SBT) of a certain point p on the grid is given by:

${SBT}_{p} = {\frac{1}{{CET}({Bolus})}{\int_{T\; 2}^{T\; 1}{{{CET}(z)}\ {z}}}}$

where CET(z) is the density at point z relative to that of water. Notethat because the initial plan is calculated with no bolus and therequirement is complete coverage of the PTV by the 90% dose surface, allSBT_(p) values will be positive in the first iteration. In subsequentiterations, SBT_(p) values are used to adjust the design of the bolusresulting from the previous iteration (FIG. 10(a)). The density isobtained from the HU to density lookup table in the planning systemwhich, in turn, was obtained during eMC commissioning from a HUcalibration phantom (Catphan, the Phantom Laboratory, Salem, N.Y.). Eachiteration of the algorithm includes calculation by the eMC algorithmsuch that subsequent modifications are based on an accurate dosedistribution.

FIG. 10 illustrates a schematic representation of bolus design algorithmafter first iteration. The lines marked with “X” indicate the previousiteration's bolus and corresponding 90% isodose line which does not yetconform well to the PTV (lines marked with “+”) in this example. Thelines marked with “*” show the bolus shape modified by the current step(a-f) (i.e., change in thickness by SBT value or a regional modulationoperator), as well as the effect of this change on the dosedistribution. For reference, lines marked with “=” denote the bolusshape and 90% isodose line from the previous step. Hot spots areindicated as circles. The individual steps are: (a) estimation of thebolus thickness based on SBT values, (b) smoothing for hot spots, (c)smoothing for dose coverage, (d) smoothing for surface irregularity, (e)adjustment at PTV margin and (f) extension outside PTV.

Regional modulation: While the calculation of SBT values largelyimproves conformity of the 90% isodose surface, it does not addresssecondary effects, such as regional hot or cold spots or the effect ofirregular bolus surface. Separate regional modulation operators aredeveloped to address: i) hot spots in the PTV, ii) undercoverage, iii)irregular bolus surface, iv) coverage at the PTV margin, and v)extension of the bolus beyond the PTV. These operators are appliedsequentially; however, we reiterate that the dose calculation isperformed only by the eMC algorithm in the planning system. Three of theoperators (i-iii) involve regional smoothing. In these cases, the SBTmatrix is segmented into regions of interest containing points p wheremodulation is required, neighboring points q that are used to smooth p,and points outside of the region of interest (FIG. 11). Three smoothingoperators are used according to the application:

${SBT}_{p} = \left\{ \begin{matrix}{{{RM}\left( {p,q,{SF},{{Mode}\; 1}} \right)} = \frac{0 + {\Sigma_{r_{pq} < {SF}}{SBT}_{q}{\exp \left( {{{- r_{pq}^{2}}/2}{SF}^{2}} \right)}}}{{1 + {\Sigma_{r_{pq} < {SF}}{\exp \left( {{{- r_{pq}^{2}}/2}{SF}^{2}} \right)}}}\;}} \\{{{RM}\left( {p,q,{SF},{{Mode}\; 2}} \right)} = \frac{{SBT}_{p} + {\Sigma_{r_{pq} < {SF}}{SBT}_{q}{\exp \left( {{{- r_{pq}^{2}}/2}{SF}^{2}} \right)}}}{1 + {\Sigma_{r_{pq} < {SF}}{\exp \left( {{{- r_{pq}^{2}}/2}{SF}^{2}} \right)}}}}\end{matrix} \right.$

where r_(pq) is the distance between p and q, and SF(mm) is thesmoothing factor, controlling the width of smoothing region and smoothlevel (i.e., 5, 10, and 20 mm for low, medium, and high).

FIG. 11 is a schematic representation of regions involved in smoothing(e.g., to alleviate a hot spot). The red line shows the projection ofthe PTV onto the calculation plane. The green line denotes the region ofinterest satisfying the hot spot criterion and containing points, p,that will be adjusted. Points q between the blue and green lines areincluded in the smoothing operation, but are not adjusted.

Smoothing for hot spot: The first modulation operator aims to alleviatethe hot spots that exist within the distribution after the previousiteration of eMC dose calculation (FIG. 10(b)). No smoothing is requiredif maximum dose is less than 110% of the prescription dose; otherwise,the hot spot region is projected to the SBT plane and smoothed.RM(Mode 1) is chosen here since the original SBT value in this criteriaregion may differ appreciably compared to the surroundings.

Smoothing for dose coverage: Although the calculation of SBT values aimsto provide full coverage by the 90% isodose surface, accurate eMCcalculation following bolus design may reveal undercoverage in certainregions of the PTV. In these regions, SBT values will be negative (i.e.,to decrease bolus thickness). However, testing of the effect of SBTadjustment alone reveals that the bolus thinning must be extendedsomewhat beyond the region defined by the projection of the under dosedarea. Accordingly, negative SBT values in the region of interest areretained, while surrounding values are smoothed (see FIG. 10(c)).RM(Mode 2) is invoked here, which will always increase target coveragesince all affected points assume negative values following theoperation.

Smoothing for potential irregular surface: Following the previousoperations, discontinuities may be present at the boundaries of regionsof interest. Surface irregularities are identified by using a gradientthreshold criterion equal to two times of the mean value of gradientmagnitude, and smoothed using RM(Mode 2) (FIG. 10(d)).

Adjustment at PTV margin: Relative to more central regions, the edge ofthe PTV receives less scattered radiation dose simply due to collimationby the electron applicator. To remedy underdosing in this region, aregion of interest is defined as a 10 mm wide border inside of theprojection of the PTV onto the SBT matrix (FIG. 10(e)). A function isapplied to reduce bolus thickness according to:

${SBT}_{p} = \left\{ \begin{matrix}{{{SBT}_{p} \times \left( {1 - {{KerfMA}\left( {\max \left( {{{K\; 1} - r_{pm}},0} \right)} \right)}} \right)},} & {{{if}\mspace{14mu} {SBT}_{p}} > 0} \\{{{SBT}_{p} \times \left( {1 - {{KerfMA}\left( {\max \left( {{{K\; 1} - r_{pm}},0} \right)} \right)}} \right)},} & {{{if}\mspace{14mu} {SBT}_{p}} < 0}\end{matrix} \right.$

where values are adjusted along radial lines from the central axis: mexists on the inner boundary of the region of interest, p exists withinthe region of interest, r_(pm) is the distance between p and m,

${{KerfMA}(x)} = {\exp \left( {- \frac{x^{2}}{2{sigma}^{2}}} \right)}$and ${K\; 1} = \sqrt{{- 2}{\ln (0.01)}{sigma}^{2}}$

(i.e., the distance over which KerfMA(x) increases from 0.01 to 1 (FIG.12)). In practice, we determine that effective values of sigma must berelated to beam profile, increasing with both energy and applicatordimension. In this work and for coding simplicity, an approximation of

sigma=√{square root over (Energy×Applicatior))}

is employed.

Shift outside PTV: The area corresponding to all ray lines between theedge of the PTV and a distance 1.0 cm beyond the electron aperture aresubject to this operator. In this region, bolus thicknesses are simplyextruded:

SBT_(p)=SBT_(n)

where n is the intersection of PTV contour and line from p to theprojection of central axis (FIG. 10(f)).

FIG. 3A illustrates an example of a 3D printed bolus 302 in place on acast of a foot 300. FIG. 3B illustrates a cutaway view of the 3D printedbolus 302 and calculated dose distribution within a patient foot 300.The PTV 306 is within a region 306 that receives the prescribed level ofthe administered radiotherapy dose, thereby focusing the radiotherapyand reducing its effects on other surrounding tissue. While this exampleshows for a bolus use with a foot, the system can receive CT scan dataof virtually any body part, and design a corresponding bolus for 3Dprinting based on that CT scan data, a desired treatment region, and adesired radiation therapy dose.

FIG. 4 illustrates an example user interface 400 for bolus design in aninitial, pre-design stage. In this example, the user selects a bolusmaterial, such as PLA, and the system uses the radiation characteristicsof that material when calculating the size and shape of the 3D-printedbolus. The user also specifies other data, such as the CT scan data ofthe patient, the desired treatment region within the CT scan data, adesired radiation treatment regime and dosage information, and so forth.The CT scan data can be in DICOM format, for example. The structure setas delineated on the CT scan data in the treatment planning system canbe represented in DICOM RT Structure format or other suitable digitalformat. The PTV structure defines within the structure set to which thedose must conform. The initial bolus object (if any) can be selectedfrom a set as defined in the treatment planning system, such as aselection from a template set of bolus shapes. The level of a hot-spotwithin the dose distribution indicates a level of compensation thatshould be performed during optimization. The user interface also allowsthe user to specify the bolus material, such as PLA, ABS, or othermaterial. The user interface allows the user to specify a resolution orgrid size to be used in the bolus optimization process. Using this dataas input, the user can then click the “RUN” button to initiate a bolusdesign. FIG. 5 illustrates the example user interface 500 after the userclicks the “RUN” button. The user interface 500 can present a virtual 3Dmodel of the bolus on the display prior to printing the 3D model. Theuser interface 500 allows the user to continue to tweak the varioussettings, such as the bolus material, and iteratively view what the3D-printed bolus will look like with updated settings. The system canprovide additional details about the bolus to be 3D printed, such asestimated weight, dimensions, time to produce, materials cost andquantity, maximum number (if any) of treatments the 3D-printed bolus israted for, and so forth. When the user is satisfied with the view of thedesign on the user interface 500, the user can output the bolus model toa 3D printer to be created.

Certain radiation treatments are directed to sensitive parts of thebody, such as radiation therapy for breast cancer. Breast tissue isdeformable and can change position and shape more than body parts withbones to support and give structure. Thus, a bolus for use withradiation therapy for breast cancer treatments may be difficult toposition. Further, certain portions of the affected region of the body,such as skin on the inframammary fold, may become irritated or haveother issues stemming from radiation treatment. To address these andother issues, the system can analyze CT scan data of the breast, and 3Dprint an immobilization support to stabilize the breast. Additionally, acustom 3D-printed bolus, as described above, can be incorporated intothe immobilization support.

FIG. 6 illustrates an example immobilization support 600 with anintegrated bolus 602. The immobilization support 600 is, in thisexample, an immobilization mesh 604 with a strap 606 that goes aroundthe patient's torso to hold the immobilization mesh 604 in place. Abolus 602 is integrated into the immobilization mesh 604. The bolus 602is not a separate part attached or affixed to the immobilization mesh604, but rather the bolus 602 and the immobilization mesh 604 arecreated as part of the same 3D printing process. The immobilization mesh604 can be a mesh, a solid container, a substantially solid container, ablock with a cavity in to which the breast (or other body part) isinserted as part of treatment, and so forth. The mesh 604 is shown hereas one example. Because the immobilization mesh 604 is generated basedon CT scan data, the immobilization mesh 604 fits the dimensions of thepatient in a very precise manner. In this way, when the patient wearsthe immobilization support 600, the patient's breast is supported toavoid damage or irritation to the inframammary fold 608, and the breasttissue is immobilized so the bolus is in the same position for eachtreatment session in a periodic treatment regime. Thus, the radiationtreatment is administered consistently to the same region of the breastin a manner that accurately reflects the dose distribution createdduring treatment planning. The breast is immobilized into the sameposition, and the bolus is in the same position relative to theimmobilized breast. The integrated immobilization mesh 604 and bolus 602allows only minimal dose build up over area of immobilization, i.e. thearea of the mesh 604 other than the bolus 602. The bolus 602 is designedin a patient-specific way to enable precise and consistent radiationtreatment for that patient's body. Further, this approach can reducelabor requirements associated with designing, fitting, and placing thebolus as part of a radiation therapy regime. The bolus 602 on theimmobilization support 600 can be designed for any of the threedifferent types of radiation outlined above: photon, electron, andproton. While the example provided herein relates to breast tissue, asimilar approach with an immobilization mesh 604 and integrated3D-printed bolus 602 can be applied to virtually any other body parts,such as head and neck, scalp, ankles, and other extremities.

The system can, when designing such a 3D-printed immobilization support600 and integrated bolus 602, reduce of build-up effect outside of thebolus area. The system can control various aspects of the immobilizationmesh 604, such as the mesh density or size of cells in the mesh, thethickness of the ‘lines’ of 3D-printed material in the mesh, oreffective electron density of the 3D-printed material (sometimes called‘infill’ in 3D printing terminology). In one variation, theimmobilization support 600 can be 3D printed to include brackets orgrommets or some other attachment for connecting the strap 606.

In a progressively changing radiation treatment, the system can receiveCT scan data (or other body imaging data) of the patient, and design aseries of immobilization meshes 604 and boluses 602 for different stagesof the treatment plan. For example, the treatment plan may include ahigh dose of electron radiation for weeks 1 and 2, while the electronradiation dose is lowered for weeks 3 and 4. The system can design, and3D-print on-demand (such as the night before an appointment at which anew bolus is required), a first combination immobilization mesh 604 andbolus 602 for weeks 1 and 2, and a second combination immobilizationmesh 604 and bolus 602 for weeks 3 and 4. Each combination is based onthe same patient CT scan data, but incorporates a bolus 602 of adifferent shape, size, type, and/or in a different position on theimmobilization mesh 604. Additionally, the system can incorporatefeedback from the treatment progress and revise yet-unprinted ones inthe series to be tailored for the changing radiation therapy needs andthe body's changing reactions to the radiation therapy.

When applying radiation therapy, doctors (or others) often wish to knowwhether the radiation is being administered properly, and how muchradiation is being administered, among other data points. A 3D-printedbolus can include several mechanisms for collecting this data. Forexample, a 3D-printed bolus can be designed so that the 3D printingprocess creates (or leaves) a specific cavity or cavities in the bolusfor receiving radiation dosimeters. A doctor or other user can insert aradiation dosimeter into the cavity in the bolus prior to treatment togather data during treatment, then can remove the radiation dosimeterafter treatment. The shape of the cavity can be tailored for a specifickind of dosimeter, so only the correct type of dosimeter(s) will fit.The cavity can be virtually any shape, and can optionally includelatches, brackets, or other restraining mechanism to position thedosimeter and retain it in place. Because the 3D design and printingprocess allows full control of the 3D design of the bolus, dosimeterscan be embedded within the bolus to enable in vivo dosimetry. Exampledosimeters include ionization chambers, diodes,metal-oxide-semiconductor field-effect transistors (MOSFETs),radiographic film, radiochromic film, diamond detectors, opticallystimulated luminescence dosimeters (OSLDs), or arrays thereof. Becausethe bolus is in direct contact with the skin, the dosimeters can also beplaced proximal to the skin surface (or very close to the skin surfacewithin or on the bolus) to allow real-time readout of the radiation dosereceived by the skin during treatment.

In one embodiment, the material making up the bolus can itself be a sortof dosimeter. Certain materials are scintillators, or materials whichexhibit scintillation, the property of luminescence when excited byionizing radiation, such as PET or PEN plastics that are 3D-printable.Scintillators can be organic crystals or liquids, inorganic crystals,specialized glass, as well as plastic scintillators. Plasticscintillators typically include a scintillator (or fluor) suspended in apolymer base. As the 3D printer creates the bolus, all the material fromwhich the bolus is created can include one or more scintillatormaterials. Then, as the bolus is used in the radiation therapy, thescintillators react and fluoresce. The bolus can include different kindsof scintillators triggered at different radiation levels. Thus, thetype, amount, or position of scintillator reacting can provide anindication of the quantity and location of the administered radiation.The 3D printer can also incorporate different scintillators in differentregions of the bolus. The 3D printer can incorporate scintillators inthe bolus in patterns that form words or symbols when a suitableradiation dose is applied to the bolus. For example, the majority of thebolus material is a non-scintillator, and during 3D printing, certainregions of the bolus are constructed with scintillator materials inpatterns that fluoresce when exposed to a specific amount of radiation.Then, when the bolus is used for treatment, the patterns of scintillatormaterials embedded in the bolus fluoresce. In one example, a pattern ofscintillator material in the shape of a smiley face, a checkmark, or theword “YES” can fluoresce when the radiation is at a desired level.Conversely, patterns of scintillator materials embedded in the bolus canalso indicate when the dose is too low or too high with differentpatterns, such as a letter “X” or a frowny face. With respect to theimmobilization mesh 604, the 3D printer can also include scintillatorsin the immobilization mesh 604 to provide a visual indication of whetherthe dose of radiation is insufficient or is too high.

While the primary embodiment discussed herein is a bolus that is indirect contact with the skin of a patient, similar 3D-printingapproaches and algorithms can be adapted for other, related uses thatcustom adapt a radiation dose for a patient but that are not in directcontact with the skin of the patient. For example, instead of analgorithm for shaping a bolus to be applied to a patient's skin in orderto deliver a desired radiation dose, a similar design process andsimilar algorithm can be applied to design a custom proton compensatorto be positioned upstream in a proton radiation beam. Such a protoncompensator would not be in direct contact with the patient's skin, butwould be upstream. When in position for the proton radiation beam, thecustom, patient-specific proton compensator modulates the depth of thehigh dose deposited as a function of position across the beam so thatthe desired amount of proton radiation is delivered and that thetherapeutic dose distribution conforms to the curvature of the deepaspect of the tumor volume. Radiation treatment can include acombination of a proton compensator upstream and a bolus in contact withthe patient's skin.

FIG. 7 illustrates an example method embodiment. The operationspresented herein are examples. The method embodiment can includeadditional steps, remove certain steps, perform the steps in differentorders than what is presented herein, and can perform the steps in anycombination or permutation. A system configured to practice the examplemethod collects three-dimensional scan data of a target radiationtreatment area of a user (702). The system performs a first dosecalculation for a treatment goal for the target radiation treatment areawithout a bolus (704). The dose calculations can be based on an electronMonte Carlo (eMC) algorithm. The system creates, based on thethree-dimensional scan data, the target radiation treatment area, andthe dose calculation, a model for a target bolus (706).

The system performs a second dose calculation for the treatment goal forthe target radiation treatment area based on the model for the targetbolus (708). When the second dose calculation satisfies conditionsassociated with the treatment goal, the system can output the model forthe target bolus to a fabrication device to produce a replica of thetarget bolus for use with the target radiation treatment area of theuser. If the second dose calculation does not satisfy the conditionsassociated with the treatment goal, the system can perform an analysisof the model for the target bolus for at least one of a hot spot, a coolspot, dose coverage, surface irregularity, a margin of a planning targetvolume, or conformity at edges of the planning target volume. Based onthe analysis, the system can revise the model to yield a revised model,and output the revised model to the fabrication device to produce thereplica of the target bolus for use with the target radiation treatmentarea of the user. The replica can be made up of polylactic acid, or someother material suitable for use with a 3D printer. The system caniterate the analysis and revising the model until the revised modelsatisfies the conditions associated with the treatment goal. Thefabrication device can be a 3D printer. The model can be an STL file.The system can present or render the model in a user interface prior tofabrication via the 3D printer.

After the bolus is 3D printed, the system can verify that it satisfiesthe conditions associated with the treatment goal based on a computedtomography scan of the bolus while placed on the target radiationtreatment area of the user. The system can similarly gather radiationdata via dosimeters embedded in the bolus, inserted into the bolus, orvia scintillators that are part of the bolus material.

The patient-facing side of the bolus is shaped to conform to a surfaceof the target radiation treatment area. The beam-incident side of thereplica can be shaped to a regular geometric surface or to some othershape or contour such that radiation passed through the bolus isdelivered in a desired dosage to a desired portion of the skin or bodyof the user when placed on the target radiation treatment area of theuser and a radiation beam is applied to the target radiation treatmentarea of the user through the bolus. The bolus can be reusable formultiple radiation treatment sessions.

Various embodiments of the disclosure are described in detail herein.While specific implementations are described, it should be understoodthat this is done for illustration purposes only. Other components andconfigurations may be used without parting from the spirit and scope ofthe disclosure.

With reference to FIG. 8, an exemplary system and/or computing device800 includes a processing unit (CPU or processor) 820 and a system bus810 that couples various system components including the system memory830 such as read only memory (ROM) 840 and random access memory (RAM)850 to the processor 820. The system 800 can include a cache 822 ofhigh-speed memory connected directly with, in close proximity to, orintegrated as part of the processor 820. The system 800 copies data fromthe memory 830 and/or the storage device 860 to the cache 822 for quickaccess by the processor 820. In this way, the cache provides aperformance boost that avoids processor 820 delays while waiting fordata. These and other modules can control or be configured to controlthe processor 820 to perform various operations or actions. Other systemmemory 830 may be available for use as well. The memory 830 can includemultiple different types of memory with different performancecharacteristics. It can be appreciated that the disclosure may operateon a computing device 800 with more than one processor 820 or on a groupor cluster of computing devices networked together to provide greaterprocessing capability. The processor 820 can include any general purposeprocessor and a hardware module or software module, such as module 1862, module 2 864, and module 3 866 stored in storage device 860,configured to control the processor 820 as well as a special-purposeprocessor where software instructions are incorporated into theprocessor. The processor 820 may be a self-contained computing system,containing multiple cores or processors, a bus, memory controller,cache, etc. A multi-core processor may be symmetric or asymmetric. Theprocessor 820 can include multiple processors, such as a system havingmultiple, physically separate processors in different sockets, or asystem having multiple processor cores on a single physical chip.Similarly, the processor 820 can include multiple distributed processorslocated in multiple separate computing devices, but working togethersuch as via a communications network. Multiple processors or processorcores can share resources such as memory 830 or the cache 822, or canoperate using independent resources. The processor 820 can include oneor more of a state machine, an application specific integrated circuit(ASIC), or a programmable gate array (PGA) including a field PGA.

The system bus 810 may be any of several types of bus structuresincluding a memory bus or memory controller, a peripheral bus, and alocal bus using any of a variety of bus architectures. A basicinput/output (BIOS) stored in ROM 840 or the like, may provide the basicroutine that helps to transfer information between elements within thecomputing device 800, such as during start-up. The computing device 800further includes storage devices 860 or computer-readable storage mediasuch as a hard disk drive, a magnetic disk drive, an optical disk drive,tape drive, solid-state drive, RANI drive, removable storage devices, aredundant array of inexpensive disks (RAID), hybrid storage device, orthe like. The storage device 860 can include software modules 862, 864,866 for controlling the processor 820. The system 800 can include otherhardware or software modules. The storage device 860 is connected to thesystem bus 810 by a drive interface. The drives and the associatedcomputer-readable storage devices provide nonvolatile storage ofcomputer-readable instructions, data structures, program modules andother data for the computing device 800. In one aspect, a hardwaremodule that performs a particular function includes the softwarecomponent stored in a tangible computer-readable storage device inconnection with the necessary hardware components, such as the processor820, bus 810, display 870, and so forth, to carry out a particularfunction. In another aspect, the system can use a processor andcomputer-readable storage device to store instructions which, whenexecuted by the processor, cause the processor to perform operations, amethod or other specific actions. The basic components and appropriatevariations can be modified depending on the type of device, such aswhether the device 800 is a small, handheld computing device, a desktopcomputer, or a computer server. When the processor 820 executesinstructions to perform “operations”, the processor 820 can perform theoperations directly and/or facilitate, direct, or cooperate with anotherdevice or component to perform the operations.

Although the exemplary embodiment(s) described herein employs the harddisk 860, other types of computer-readable storage devices which canstore data that are accessible by a computer, such as magneticcassettes, flash memory cards, digital versatile disks (DVDs),cartridges, random access memories (RAMs) 850, read only memory (ROM)840, a cable containing a bit stream and the like, may also be used inthe exemplary operating environment. Tangible computer-readable storagemedia, computer-readable storage devices, or computer-readable memorydevices, expressly exclude media such as transitory waves, energy,carrier signals, electromagnetic waves, and signals per se.

To enable user interaction with the computing device 800, an inputdevice 890 represents any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 870 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems enable a user to provide multiple types of input to communicatewith the computing device 800. The communications interface 880generally governs and manages the user input and system output. There isno restriction on operating on any particular hardware arrangement andtherefore the basic hardware depicted may easily be substituted forimproved hardware or firmware arrangements as they are developed.

For clarity of explanation, the illustrative system embodiment ispresented as including individual functional blocks including functionalblocks labeled as a “processor” or processor 820. The functions theseblocks represent may be provided through the use of either shared ordedicated hardware, including, but not limited to, hardware capable ofexecuting software and hardware, such as a processor 820, that ispurpose-built to operate as an equivalent to software executing on ageneral purpose processor. For example the functions of one or moreprocessors presented in FIG. 8 may be provided by a single sharedprocessor or multiple processors. (Use of the term “processor” shouldnot be construed to refer exclusively to hardware capable of executingsoftware.) Illustrative embodiments may include microprocessor and/ordigital signal processor (DSP) hardware, read-only memory (ROM) 840 forstoring software performing the operations described below, and randomaccess memory (RAM) 850 for storing results. Very large scaleintegration (VLSI) hardware embodiments, as well as custom VLSIcircuitry in combination with a general purpose DSP circuit, may also beprovided.

The logical operations of the various embodiments are implemented as:(1) a sequence of computer implemented steps, operations, or proceduresrunning on a programmable circuit within a general use computer, (2) asequence of computer implemented steps, operations, or proceduresrunning on a specific-use programmable circuit; and/or (3)interconnected machine modules or program engines within theprogrammable circuits. The system 800 shown in FIG. 8 can practice allor part of the recited methods, can be a part of the recited systems,and/or can operate according to instructions in the recited tangiblecomputer-readable storage devices. Such logical operations can beimplemented as modules configured to control the processor 820 toperform particular functions according to the programming of the module.For example, FIG. 8 illustrates three modules Mod1 862, Mod2 864 andMod3 866 which are modules configured to control the processor 820.These modules may be stored on the storage device 860 and loaded intoRAM 850 or memory 830 at runtime or may be stored in othercomputer-readable memory locations.

One or more parts of the example computing device 800, up to andincluding the entire computing device 800, can be virtualized. Forexample, a virtual processor can be a software object that executesaccording to a particular instruction set, even when a physicalprocessor of the same type as the virtual processor is unavailable. Avirtualization layer or a virtual “host” can enable virtualizedcomponents of one or more different computing devices or device types bytranslating virtualized operations to actual operations. Ultimatelyhowever, virtualized hardware of every type is implemented or executedby some underlying physical hardware. Thus, a virtualization computelayer can operate on top of a physical compute layer. The virtualizationcompute layer can include one or more of a virtual machine, an overlaynetwork, a hypervisor, virtual switching, and any other virtualizationapplication.

The processor 820 can include all types of processors disclosed herein,including a virtual processor. However, when referring to a virtualprocessor, the processor 820 includes the software components associatedwith executing the virtual processor in a virtualization layer andunderlying hardware necessary to execute the virtualization layer. Thesystem 800 can include a physical or virtual processor 820 that receiveinstructions stored in a computer-readable storage device, which causethe processor 820 to perform certain operations. When referring to avirtual processor 820, the system also includes the underlying physicalhardware executing the virtual processor 820.

Embodiments within the scope of the present disclosure may also includetangible and/or non-transitory computer-readable storage devices forcarrying or having computer-executable instructions or data structuresstored thereon. Such tangible computer-readable storage devices can beany available device that can be accessed by a general purpose orspecial purpose computer, including the functional design of any specialpurpose processor as described above. By way of example, and notlimitation, such tangible computer-readable devices can include RAM,ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storageor other magnetic storage devices, or any other device which can be usedto carry or store desired program code in the form ofcomputer-executable instructions, data structures, or processor chipdesign. When information or instructions are provided via a network oranother communications connection (either hardwired, wireless, orcombination thereof) to a computer, the computer properly views theconnection as a computer-readable medium. Thus, any such connection isproperly termed a computer-readable medium. Combinations of the aboveshould also be included within the scope of the computer-readablestorage devices.

Computer-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. Computer-executable instructions also includeprogram modules that are executed by computers in stand-alone or networkenvironments. Generally, program modules include routines, programs,components, data structures, objects, and the functions inherent in thedesign of special-purpose processors, etc. that perform particular tasksor implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of the program code means for executing steps of the methodsdisclosed herein. The particular sequence of such executableinstructions or associated data structures represents examples ofcorresponding acts for implementing the functions described in suchsteps.

Other embodiments of the disclosure may be practiced in networkcomputing environments with many types of computer systemconfigurations, including personal computers, hand-held devices,multi-processor systems, microprocessor-based or programmable consumerelectronics, network PCs, minicomputers, mainframe computers, and thelike. Embodiments may also be practiced in distributed computingenvironments where tasks are performed by local and remote processingdevices that are linked (either by hardwired links, wireless links, orby a combination thereof) through a communications network. In adistributed computing environment, program modules may be located inboth local and remote memory storage devices.

The various embodiments described above are provided by way ofillustration only and should not be construed to limit the scope of thedisclosure. For example, the principles herein can be applied to anyclinical case involving electron beam therapy. The 3D printing processcan also apply to x-ray photon beam therapy over multiple sites wherethe tumor volume is superficial, although the design process for thebolus may be modified somewhat for photons. The bolus design algorithmcan be changed, for example, to support photon or proton transportinstead of electron transport. The eMC algorithm in 202, 206, and 214can be replaced by a megavoltage photon dose calculation algorithm.Various modifications and changes may be made to the principlesdescribed herein without following the example embodiments andapplications illustrated and described herein, and without departingfrom the spirit and scope of the disclosure. Claim language reciting “atleast one of” a set indicates that one member of the set or multiplemembers of the set satisfy the claim.

We claim:
 1. A method comprising: collecting three-dimensional scan dataof a target radiation treatment area of a user; performing a first dosecalculation for a treatment goal for the target radiation treatment areawithout a bolus; creating, via a processor and based on thethree-dimensional scan data, the target radiation treatment area, andthe dose calculation, a model for a target bolus; and performing asecond dose calculation for the treatment goal for the target radiationtreatment area based on the model for the target bolus.
 2. The method ofclaim 1, further comprising: when the second dose calculation satisfiesconditions associated with the treatment goal, outputting the model forthe target bolus to a fabrication device to produce a replica of thetarget bolus for use with the target radiation treatment area of theuser.
 3. The method of claim 1, wherein the dose calculation is based onan electron Monte Carlo algorithm.
 4. The method of claim 1, the methodfurther comprising: if the second dose calculation does not satisfy theconditions associated with the treatment goal: performing an analysis ofthe model for the target bolus for at least one of a hot spot, a coolspot, dose coverage, surface irregularity, a margin of a planning targetvolume, or conformity at edges of the planning target volume; based onthe analysis, revising the model to yield a revised model; andoutputting the revised model to the fabrication device to produce thereplica of the target bolus for use with the target radiation treatmentarea of the user.
 5. The method of claim 4, further comprising:iterating performing the analysis and revising the model until revisedmodel satisfies the conditions associated with the treatment goal. 6.The method of claim 1, wherein the fabrication device comprises athree-dimensional printer.
 7. The method of claim 6, wherein the modelfor the target bolus is represented as an STL file.
 8. The method ofclaim 6, wherein the replica comprises polylactic acid.
 9. The method ofclaim 1, further comprising: verifying that the replica satisfies theconditions associated with the treatment goal based on a computedtomography scan of the replica while placed on the target radiationtreatment area of the user.
 10. The method of claim 1, wherein apatient-facing side of the replica is shaped to conform to a surface ofthe target radiation treatment area.
 11. The method of claim 1, whereina beam-incident side of the replica is shaped to a regular geometricsurface.
 12. The method of claim 1, further comprising: placing thereplica on the target radiation treatment area of the user; and applyinga radiation beam to the target radiation treatment area of the userthrough the replica.
 13. The method of claim 12, wherein the radiationbeam comprises at least one of a megavoltage radiation beam, an electronbeam, a proton beam, or a photon beam.
 14. A system comprising: aprocessor; and a computer-readable storage device storing instructionswhich, when executed by the processor, cause the processor to performoperations comprising: receiving three-dimensional scan data of a targetarea of a user for radiation treatment; receiving a desired radiationdose for the radiation treatment; calculating, based on thethree-dimensional scan data, the desired radiation dose, andcharacteristics of a radiation source, a three-dimensional bolus modelsuch that when the radiation source is directed at the target area via abolus created according to the three-dimensional bolus model, thedesired radiation dose is administered to the target area; and creatinga bolus according to the three-dimensional bolus model via athree-dimensional printer.
 15. The system of claim 14, wherein thethree-dimensional bolus model further comprises an immobilizationcomponent to immobilize a region of the user proximate to the targetarea.
 16. The system of claim 15, wherein the immobilization componentfits contours of the region to be immobilized.
 17. The system of claim15, wherein the immobilization component comprises a mesh.
 18. Acomputer-readable storage device storing instructions which, whenexecuted by a computing device, cause the computing device to performoperations comprising: receiving three-dimensional scan data of a targetarea of a user for radiation treatment; receiving a desired radiationdose for the radiation treatment; calculating, based on thethree-dimensional scan data, the desired radiation dose, andcharacteristics of a radiation source, a three-dimensional bolus modelsuch that when the radiation source is directed at the target area via abolus created according to the three-dimensional bolus model, thedesired radiation dose is administered to the target area; and creatinga bolus according to the three-dimensional bolus model via athree-dimensional printer.
 19. The computer-readable storage device ofclaim 18, wherein the three-dimensional bolus model comprises at leastone cavity configured to receive a dosimeter.
 20. The computer-readablestorage device of claim 18, wherein the bolus is created out of amaterial that exhibits scintillation when excited by the radiationtreatment.